scholarly journals Depressive episodes–evidence for a causal role of primary anxiety disorders?

2003 ◽  
Vol 18 (8) ◽  
pp. 384-393 ◽  
Author(s):  
Hans-Ulrich Wittchen ◽  
Katja Beesdo ◽  
Antje Bittner ◽  
Renee D. Goodwin
Keyword(s):  
Risk Factors ◽  
Anxiety Disorders ◽  
Depressive Disorders ◽  
Common Mental Disorders ◽  
Future Research ◽  
Severe Impairment ◽  
First Onset ◽  
Depressive Episodes ◽  
Course Of Depression

AbstractAnxiety and depressive disorders are common mental disorders in general population, imposing tremendous burden on both affected persons and society. Moreover, comorbidity between anxiety and depressive conditions is high, leading to substantial disability and functional impairment. Findings consistently suggest that anxiety disorders are primary to depression in the majority of comorbid cases. Yet, the question of whether anxiety disorders are risk factors for depression, and potentially even causal risk factors for the first onset of depression, remains unresolved. Recent results have shown that anxiety disorders increase the risk for subsequent depression, and also affect the course of depression, resulting in a poorer prognosis. Further, some results suggest a dose–response-relationship in revealing that a higher number of anxiety disorders and more severe impairment associated with anxiety disorders additionally increase the risk for subsequent depression. The goal of this paper is to review recent literature, summarize implications of previous findings, and suggest directions for future research regarding preventive and intervention strategies.

The role of internalizing and externalizing liability factors in accounting for gender differences in the prevalence of common psychopathological syndromes

2007 ◽  
Vol 38 (1) ◽  
pp. 51-61 ◽  
Author(s):  
Mark D. Kramer ◽  
Robert F. Krueger ◽  
Brian M. Hicks
Keyword(s):  
Gender Differences ◽  
Common Mental Disorders ◽  
Future Research ◽  
Latent Factor ◽  
Gender Invariance ◽  
Co Morbidity ◽  
Best Fitting ◽  
Invariance Model ◽  
Internalizing And Externalizing

BackgroundWe hypothesized that gender differences in average levels on the internalizing and externalizing factors that account for co-morbidity among common psychopathological syndromes in both men and women account for gender differences in the prevalence of specific syndromes.MethodThe latent structure of 11 syndromes was examined in a middle-aged (mean age=52.66 years, s.d.=5.82) sample of 2992 (37% men) members of the community-based Minnesota Twin Registry (MTR) assessed using 10 scales of the Psychiatric Diagnostic Screening Questionnaire (PDSQ) and an adult antisocial behavior scale. Confirmatory factorial invariance models were applied to a best-fitting, internalizing–externalizing model.ResultsA ‘strong gender invariance model’ fit best, indicating that gender differences in the means of individual syndromes were well accounted for by gender differences in mean levels of internalizing and externalizing. Women exhibited higher mean levels of internalizing (d=0.23) and lower mean levels of externalizing (d=−0.52) than men.ConclusionsThese findings suggest that risk factors for common mental disorders exhibiting gender differences may influence prevalence at the latent factor level. Future research may benefit from focusing on both the latent factor and individual syndrome levels in explaining gender differences in psychopathology.

Self-Directed Approaches to the Treatment of Depression

2016 ◽  
pp. 468-477
Author(s):  
Pim Cuijpers ◽  
Annet Kleiboer
Keyword(s):  
Depressive Disorders ◽  
Future Research ◽  
Evidence Based ◽  
Advantages And Disadvantages ◽  
Self Help ◽  
Treatment Of Depression ◽  
High Prevalence ◽  
Evidence Based Treatments ◽  
The Common

This article examines self-directed approaches to the treatment of depression. It first considers some of the reasons why the uptake of mental health services by depressed people is low, despite the high prevalence of depressive disorders and the availability of evidence-based treatments. It then looks at the role of self-management in increasing access to evidence-based treatments for depression. It also defines what self-directed treatments are and goes on to discuss the different types of self-directed therapy, the common components of self-directed interventions for depression, Internet-based interventions for depression, and the advantages and disadvantages of self-directed interventions. Finally, it summarizes the findings from research on self-directed interventions for depression and suggests directions for future research and development in this area. Some titles of self-help books that can be used in self-directed interventions are presented.

scholarly journals Exploring the Role of Endothelial Cell Resilience in Cardiovascular Health and Disease

2020 ◽  
Author(s):  
Yunling Gao ◽  
Zorina S. Galis
Keyword(s):  
Risk Factors ◽  
Paradigm Shift ◽  
Cardiovascular Health ◽  
Research Effort ◽  
Future Research ◽  
Therapeutic Approaches ◽  
New Knowledge ◽  
Health And Disease ◽  
Disease Understanding

Traditionally, much research effort has been invested into focusing on disease, understanding pathogenic mechanisms, identifying risk factors, and developing effective treatments. A few recent studies unraveling the basis for absence of disease, including cardiovascular disease, despite existing risk factors, a phenomenon commonly known as resilience, are adding new knowledge and suggesting novel therapeutic approaches. Given the central role of endothelial function in cardiovascular health, we herein provide a number of considerations that warrant future research and considering a paradigm shift toward identifying the molecular underpinnings of endothelial resilience.

The Comorbidity of Anxiety Disorders with Depression and the Associated Risk Factors in Geriatric Psychiatry Outpatients

2009 ◽  
Vol 24 (S1) ◽  
pp. 1-1
Author(s):  
F. Beskardes ◽  
T. Ertan ◽  
E. Eker
Keyword(s):  
Risk Factors ◽  
Depressive Disorder ◽  
Anxiety Disorders ◽  
Depressive Disorders ◽  
Depression Scale ◽  
Geriatric Psychiatry ◽  
Major Depressive ◽  
Outpatient Unit ◽  
Prevalence Of Depression ◽  
Associated Risk Factors

Aims:We aimed to study the prevalence of anxiety disorders with the comorbidity of depressive disorders and the effects of risk factors among the patients attending the general Geriatric Psychiatry Outpatient Unit.Methods:Subjects were evaluated in terms of Anxiety Disorders on the basis of DSM criteria, SCID. Each patient was asked to fill out Spielberger State-Trait Anxiety Scale, Beck Anxiety and Depression Scale. Sociodemographic features and risk factors were assesed the prepared questionnaire.Results:In a number of total 1209 applicants in 12 months, we found the prevalance of anxiety disorders was %9,48 with a number of 115 patients in outpatient department applications and the prevalence of Generalized Anxiety Disorder was found out to be %4,63(n:56), Panic Disorder with Agoraphobia %1,98(n:24), without Agoraphobia %0,90(n:11), the prevalence of OCD was %0,82(n:10), PTSD %0,49(n:6) and other anxiety disorders (SAD, SP, NOS) was %0,66(n:8).In the patients with anxiety disorders, the prevalence of depression comorbidity was found out to be %73,05(n:84), with the prevalence of the comorbid major depressive disorder %26,1(n:31), and the dysthymic/minor depressive disorder was %46,95(n:53). As a result of statistical analysis,we found that the risk factors associated with STAI-I and II scores were total years spent on education, but in reverse manners, as the education level increased, the STAI-I and II scores decreased.Conclusions:Anxiety disorders with comorbid depression might be frequent disorders among Turkish secondary care attenders. There is a need for further studies on the epidemiology of anxiety disorders and their comorbidity with depression among elderly in Turkey.

scholarly journals Prospective predictors of first-onset depressive disorders in adolescent females with anxiety disorders

2018 ◽  
Vol 235 ◽  
pp. 176-183 ◽  
Author(s):  
Estee M. Hausman ◽  
Roman Kotov ◽  
Greg Perlman ◽  
Greg Hajcak ◽  
Ellen M. Kessel ◽  
...  
Keyword(s):  
Anxiety Disorders ◽  
Depressive Disorders ◽  
Adolescent Females ◽  
First Onset

scholarly journals Network Analysis of the Symptoms of Depressive Disorders Over the Course of Therapy: Changes in Centrality Measures

2021 ◽  
Vol 18 (1) ◽  
pp. 48-58
Author(s):  
Seon-Cheol Park ◽  
Yaeseul Kim ◽  
Kiwon Kim ◽  
Young Sup Woo ◽  
Jung-Bum Kim ◽  
...  
Keyword(s):  
Network Analysis ◽  
Depressive Disorders ◽  
Rating Scale ◽  
Initial Period ◽  
Centrality Measures ◽  
Clinical Research Center ◽  
Hamd Score ◽  
First Onset ◽  
Using Data ◽  
Depressive Episodes

Objective Network analysis can be used in terms of a novel psychopathological approach for depressive syndrome. We aimed to estimate the successive network structures of depressive symptoms in patients with depressive disorder using data from the Clinical Research Center for Depression study.Methods We enrolled 1,152 South Korean adult patients with depressive disorders who were beginning treatment for first-onset or recurrent depressive episodes. We examined the network structure of the severities of the items on the Hamilton Depression Rating Scale (HAMD) at baseline and at weeks 2, 12, 25, and 52. The node strength centrality of all the HAMD items at baseline and at week 2, 12, 25, and 52 in terms of network analysis.Results In the severity networks, the anxiety (psychic) item was the most centrally situated in the initial period (baseline and week 2), while loss of weight was the most centrally situated item in the later period (weeks 25 and 52). In addition, the number of strong edges (i.e., edges representing strong correlations) increased in the late period compared to the initial period.Conclusion Our findings support a period-specific and symptom-focused therapeutic approach that can provide complementary information to the unidimensional total HAMD score.

Dynamic risk for first onset of depressive disorders in adolescence: does change matter?

2021 ◽  
pp. 1-9
Author(s):  
Wenting Mu ◽  
Kaiqiao Li ◽  
Yuan Tian ◽  
Greg Perlman ◽  
Giorgia Michelini ◽  
...  
Keyword(s):  
Risk Factors ◽  
Depressive Disorders ◽  
Cox Regression ◽  
Average Level ◽  
Risk Level ◽  
Social Risk ◽  
Dynamic Risk ◽  
First Onset ◽  
Time Varying Covariates ◽  
Chronic Risk

Abstract Background Risk factors for depressive disorders (DD) change substantially over time, but the prognostic value of these changes remains unclear. Two basic types of dynamic effects are possible. The ‘Risk Escalation hypothesis’ posits that worsening of risk levels predicts DD onset above average level of risk factors. Alternatively, the ‘Chronic Risk hypothesis’ posits that the average level rather than change predicts first-onset DD. Methods We utilized data from the ADEPT project, a cohort of 496 girls (baseline age 13.5–15.5 years) from the community followed for 3 years. Participants underwent five waves of assessments for risk factors and diagnostic interviews for DD. For illustration purposes, we selected 16 well-established dynamic risk factors for adolescent depression, such as depressive and anxiety symptoms, personality traits, clinical traits, and social risk factors. We conducted Cox regression analyses with time-varying covariates to predict first DD onset. Results Consistently elevated risk factors (i.e. the mean of multiple waves), but not recent escalation, predicted first-onset DD, consistent with the Chronic Risk hypothesis. This hypothesis was supported across all 16 risk factors. Conclusions Across a range of risk factors, girls who had first-onset DD generally did not experience a sharp increase in risk level shortly before the onset of disorder; rather, for years before onset, they exhibited elevated levels of risk. Our findings suggest that chronicity of risk should be a particular focus in screening high-risk populations to prevent the onset of DDs. In particular, regular monitoring of risk factors in school settings is highly informative.

Anxiety Disorders: Similarities and Differences of Comorbidity in Treated and Untreated Groups

1991 ◽  
Vol 159 (S12) ◽  
pp. 23-33 ◽  
Author(s):  
Hans-Ulrich Wittchen ◽  
Cecilia Ahmoi Essau ◽  
Jürgen-Christian Krieg
Keyword(s):  
Anxiety Disorders ◽  
Depressive Disorders ◽  
Age Of Onset ◽  
Clinical Sample ◽  
Clinical Samples ◽  
Max Planck ◽  
Two Samples ◽  
Similarities And Differences ◽  
Depressive Episodes

The similarities and differences of comorbidity in treated and untreated samples with anxiety disorders were examined using data from the Munich Follow-up Study: 133 subjects with anxiety and depressive disorders and 101 former in-patients at the Max Planck Institute for Psychiatry. Diagnoses were based on the DIS, not using the optional DSM—III exclusion rules. In these epidemiological and clinical samples, 69% and 95% respectively had at least two diagnoses. The epidemiological sample was clearly differentiated from the clinical sample by age of onset. The development of both depressive episodes and substance disorders in the two samples was mostly secondary to the development of anxiety problems. The outcome for subjects with both anxiety and depressive disorders tended to be worse than that for those with anxiety alone, regardless of whether a depressive episode was present at the time of the follow-up investigation. The usefulness is underlined of the comorbidity concept based on operationalised diagnosis without the exclusion rules offered by DSM—III and DSM—III—R.

scholarly journals Psychological risk factors and the course of depression and anxiety disorders: A review of 15 years of NESDA research

2021 ◽  
Author(s):  
Sascha Y. Struijs ◽  
Peter J. de Jong ◽  
Bertus F. Jeronimus ◽  
Willem van der Does ◽  
Harriëtte Riese ◽  
...  
Keyword(s):  
Risk Factors ◽  
Anxiety Disorders ◽  
Depression And Anxiety ◽  
Psychological Risk Factors ◽  
Psychological Risk ◽  
Course Of Depression

A meta-analysis of poststroke depression risk factors comparing depressive-related factors versus others

2020 ◽  
Vol 32 (11) ◽  
pp. 1331-1344
Author(s):  
Rebecca Perrain ◽  
Lila Mekaoui ◽  
David Calvet ◽  
Jean-Louis Mas ◽  
Philip Gorwood
Keyword(s):  
Risk Factors ◽  
Alcohol Consumption ◽  
Fixed Effects ◽  
Meta Analysis ◽  
Previous History ◽  
Negative Consequences ◽  
Poststroke Depression ◽  
History Of ◽  
Depressive Episodes

ABSTRACTObjectives:Poststroke depression (PSD) is a public health issue, affecting one-third of stroke survivors, and is associated with multiple negative consequences. Reviews tried to identify PSD risk factors with discrepant results, highlighting the lack of comparability of the analyzed studies. We carried out a meta-analysis in order to identify clinical risk factors that can predict PSD.Design:PubMed and Web of Science were searched for papers. Only papers with a strictly defined Diagnostic and Statistical Manual of Mental Disorders depression assessment, at least 2 weeks after stroke, were selected. Two authors independently evaluated potentially eligible studies that were identified by our search and independently extracted data using standardized spreadsheets. Analyses were performed using MetaWin®, the role of each variable being given as a risk ratio (RR).Results:Eighteen studies were included in the meta-analysis. Identified risk factors for PSD with RR significantly above 1 were previous history of depression (RR 2.19, confidence interval (CI) 1.52–3.15), disability (RR 2.00, CI 1.58–2.52), previous history of stroke (RR 1.68, CI 1.06–2.66), aphasia (RR 1.47, CI 1.13–1.91), and female gender (RR 1.35, CI 1.14–1.61). Fixed effects model leads to identification of two more risk factors: early depressive symptoms with an RR of 2.32 (CI 1.43–3.79) and tobacco consumption (RR 1.40, CI 1.09–1.81). Time bias was found for alcohol consumption. Sample size was significantly involved to explain the role of “alcohol consumption” and “cognitive impairment.”Conclusion:Five items were significantly predictive of PSD. It might be of clinical interest that depressive-related risk factors (such as past depressive episodes) were having the largest impact.

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